Problems Associated with Drilling Operations

Introduction

The rotary drilling rig and its components are the major vehicle of modern 

drilling activities. In this method, a downward force is applied on the drill 

bit that breaks the rock with both downward force and centrifugal force, 

thereby forming the pivotal part of an effective drilling operation. The con￾ventional practice in the oil industry is to use robust drillstring assembly 

for which large capital expenses are required. However, during any drill￾ing operation, numerous challenges are encountered, each of which can 

have significant impact on the time required to complete a drilling project. 

Often, one problem triggers another problem and snowballing of problems 

occurs, thus incapacitating the drilling process. In this process, there is no 

‘small’ or ‘large’ problem, as all problems are intricately linked to each other, 

eventually putting safety and environmental integrity in jeopardy. Any such 

impact has immeasurable financial impact beyond short-term effects on the 

‘time loss’. This chapter discusses some of the generic drilling problems, such 

as H2

S-bearing zones and shallow gas, equipment and personnel, objects 

dropped into the well, resistant beds encountered, fishing operations, 

 junk retrieve operations, and twist-off. It identifies the key areas where we 

encounter drilling problems, their root causes, and solutions related to drill￾ing methods. In well planning, the key to achieving objectives successfully 

is to design drilling programs on the basis of anticipation of potential hole 

problems rather than on caution and containment. The desired process is 

to preempt any problem, because drilling problems can be very costly after 

they occur. The most prevalent drilling problems include pipe sticking, lost 

circulation, hole deviation, pipe failures, borehole instability, mud contami￾nation, formation damage, hole cleaning, H2

S-bearing formation and shal￾low gas, and equipment and personnel-related problems.

2.1 Problems Related to Drilling 

Methods and Solutions

2.1.1 Sour Gas Bearing Zones

During drilling and workover operations, the consequences of leaks with 

sour gas or crude may be devastating. Drilling H2

S-bearing formations poses 

one of the most difficult and dangerous problems to humans and equipment. 

Personnel can be injured or even killed by relatively low concentrations of 

H2

S in a very short period of time. Equipment can experience terrible fail￾ure due to H2

S gas-induced material failure. This risk depends primarily 

on the H2

S content with the formation fluids, formation pressure, and the 

production flow rate. This information is used to assess the level of risk from 

the presence of H2

S. In addition, if this risk is known or anticipated, there 

are very specific requirements to abide by in accordance to International 

Association of Drilling Contractors (IADC) rules and regulations. All infor￾mation will ultimately lead to the requirement for special equipment, layout, 

and emergency procedures for drilling and/or workover operations.

2.1.1.1 How to Tackle H2

S

The presence of H2

S can be anticipated from previous data on the field, or 

from the region. For a wildcat, all precautionary measures should be taken, 

following IADC rules, as if H2

S will be encountered. The following steps 

and the plans should be followed while H2

S gas is encountered.

i) Planning of operations

A study should be done on geological and geographical 

information of the area. This study should include history

      of adjacent wells in order to predict the expected area where 

H2

S may be encountered. Information should be obtained 

and taken into consideration about the area and known field 

conditions, including temperatures, pressures, proposed 

well depth, and H2

S concentrations.

A mud program should be drawn up which will provide dif￾ferent pressures expected to be encountered. However, H2

S 

scavenger should also be included to reduce the reaction of 

H2

S on the drillstring and related equipment to control the 

processing of H2

S at surface. Normal practice is to maintain 

a higher than normal pH (i.e., 10.5–11) and to treat the mud 

with a suitable scavenger as soon as dissolved sulphides are 

analyzed. The contamination of water-based muds due to 

H2

S can deteriorate the mud properties at a fast rate. It is 

advisable to keep the mud moving with immediate treat￾ment to maintain the desired properties.

Maintaining a high pH or using a scavenger is not suitable 

to safeguard drilling equipment against H2

S, since in a kick 

situation the wellbore may become partially/fully devoid 

of drilling fluid, thus reducing or eliminating the ability to 

contact drillstring and wellhead and BOP components with 

scavenger. H2

S resistant materials should be considered 

for this well control condition. The BOPs must be made to 

NACE specifications that conform to the presence of H2

S.

Prior to reaching the H2

S-bearing formations, the emergency 

equipment (blowout preventer, degasser, etc.) and response 

procedures should be tested in an exercise that simulates a kick.

Wind direction should be considered for the layout of equip￾ment such as shale shakers, choke manifold, mud tanks, and 

particularly vents such as flare lines, degasser vents, mud-gas 

separator vents, and diverter lines. Wind socks on the site or 

platform should enable identification of upwind assembly 

points. For offshore operations, each assembly point should 

allow easy evacuation from the installation.

ii) Drilling equipment selection

Equipment should be selected after consideration of metallurgical proper￾ties, thus reducing the chances of failure from H2

S-induced corrosion. The 

following recommendations are to be followed for H2

S designated wells:

a. BOP stack

Metallic materials for sour-gas service should be employed.

                                         All pressure containing components of the BOP stack with 

the potential to be exposed to H2

S should be manufactured 

with the material, which meets the standard of the NACE 

MR-01-75 and API RP 53. These components include annu￾lar preventer, rams, drilling spools, the hydraulic operated 

choke line valve, and gaskets, etc.

Non-metallic materials for sour service.

Non-metallic materials for sour service should conform to 

API RP 53, Section 9. A.8. Fluoropolymers, such as Teflon 

or Ryton and fluoroelastomers, such as viton or Kalrez are 

acceptable materials.

Welding should conform to sour-gas service.

Where welding is required for component fabrication, the 

welding and the heat affected zone of the welded compo￾nents should possess essentially the same chemical and 

physical properties as the parent metals of the subcompo￾nents. These include hardness properties and impact prop￾erties where appropriate. The welding is also required to be 

free of linear defects such as cracks, undercutting, and lack 

of fusion.

Sour-gas service identification should be performed.

Components should be marked in a manner that shows their 

suitability, under NACE MR-01-75, for sour service.

Identification stamping procedures as detailed in NACE 

MR-01-75, Section 5.4 should be followed.

Transportation, rigging up, and maintenance should con￾form to sour-gas requirements.

During transportation, rigging up, and maintenance of BOP 

stacks, operating practices should be used to avoid cold tem￾perature that might induce hardening of equipment compo￾nents. Material control for replacement parts for the BOP 

stack should have specifications and quality control equiva￾lent to the original equipment.

b. Flange, bonnet cover, bolting, and nut material

Each of these intended for H2

S use should meet require￾ments prescribed in API Specification 6A section 1.4 (14th

edition).

c. Choke manifold

Piping, flanges, valves, fittings, and discharge lines (flare 

lines) used in the composition of the choke manifold 

                  assembly should contain metals and seals in accordance 

with API RP 53.

d. Degassers/mud-gas separator

The degasser should be capable of effectively removing 

entrained gases from contaminated drilling fluid circu￾lated back to the surface. The vent outlet on the degasser 

should be extended so that the extracted gas can be routed 

to a remote area for flaring or connected into the choke flare 

line. A mud-gas separator is used to extract gas containing 

H2

S from drilling fluids. This separator should be tied into a 

vent line for burning so that it cannot release the gas into the 

atmosphere close to the rig side area.

e. Flare lines

Flare lines should be installed from the degasser, choke 

manifold, and mud-gas separator according to API RP 49. 

All flare lines should be equipped with the means for con￾stant or automatic ignition.

f. Drillpipe

Because of the direct contact of drillpipe with H2

S in the 

wellbore where various temperature and pressure conditions 

exist, the lower grades of pipe should be used so as to mini￾mize hydrogen embrittlement or sulphide stress corrosion 

cracking (SSCC). Means of control to minimize hydrogen 

embrittlement and SSCC of drillpipe can also be found in 

API RP 49. Consideration may be given to the use of a drill￾string equipped with special tool joint material.

g. Monitoring equipment

Each drilling rig operating in an area known or suspected to 

produce H2

S gas should have adequate H2

S monitoring and/or 

detection equipment. It is recommended that this equipment 

should be installed 350 meters and/or one week prior to drilling 

into the H2

S zone. H2

S concentrations should be continuously 

monitored at strategic sampling positions, e.g., shale shaker, 

mud ditch, mud tank area, etc., and results transmitted both to 

the driller’s console and to the toolpusher’s office. Audible and 

visible alarms should indicate both locally and remotely when 

H2

S concentration reaches 10 ppm. Sulphide tests should be 

carried out as part of the mud testing program in areas where 

hydrogen sulphide gas (H2

S) might be encountered.

                           Mud logging unit

The mud logging unit and equipment should be located 

away from the shaker tank and a minimum of 50 meters dis￾tance should be kept from the well head.

i. Venting system

Weatherized rigs equipped with partitions permanent in 

nature should be provided with a ventilation system suffi￾cient for the removal of accumulated H2

S.

iii) Training

When drilling in an area where H2

S gas might be encountered, training of 

personnel must be carried out on the subject matter. The action should be 

taken in the event of alarm, the use of safety equipment, and escape proce￾dures whatever the likelihood of encountering H2

S. Emergency procedures 

must be practiced regularly, using realistic emergency drills.

iv) H2

S contingency planning

A contingency plan should be drawn up when H2

S is anticipated while 

drilling. The contingency plan should be developed prior to the com￾mencement of drilling operations and should include the following:

Information on the physical effects or exposure to H2

S and 

sulphur dioxide (SO2

).

Safety and training procedures should be followed and safety 

equipment will be used.

Procedures for operations when the following conditions 

exist:

pre-alarm condition

moderate danger to life

extreme danger to life

Responsibilities and duties of personnel for each operating 

condition.

Briefing areas or locations for assembly of personnel during 

extreme danger condition should be designated. At least two 

briefing areas should be established on each drilling facility. 

Of these two areas, the one upwind at any given time is the 

safe briefing area.

Evacuation plan should be in place and well rehearsed.

Plan must be in place as to who would notify the authority 

and at what stage of the incident.

    A list of emergency medical facilities, including locations 

and/or addresses and telephone numbers must be in place.

In a pre-spud meeting, the company drilling supervisor 

should review the drilling program with the drilling contrac￾tor and service contractors, outlining each party’s responsi￾bility in drilling a well, where H2

S may be encountered.

All personnel should be fully trained and the H2

S-related 

equipment should be in place when drilling at 350 meters 

above and/or one week prior to encountering a hydrogen 

sulphide zone.

Available literature should be carefully studied before draw￾ing up H2

S procedures. Recommended references are: API 

RP49 “Safe Drilling of Wells Containing Hydrogen Sulphide.”

2.1.2 Shallow Gas-Bearing Zones

Shallow gas-bearing zone is defined as any hydrocarbon-bearing zone, 

which may be encountered at a depth close to the surface or mudline. In 

generally, it is not possible to close in and contain a gas influx from a shal￾low zone because weak formation integrity may lead to breakdown and 

broaching to surface and/or mudline. This situation is particularly hazard￾ous when drilling operations continue from a fixed installation or jack￾up rig. Shallow gas-bearing zones are usually in a pressured condition. 

However, the effective increase in pore pressure due to gas gradient can 

lead to underbalance when a shallow gas zone is first penetrated.

Shallow gas may be encountered at any time in any region of the world. 

The only way to control this problem is that we should never shut in the 

well. It is also needed to divert the gas flow through a diverter system at 

the BOP. High-pressure shallow gas can be encountered at depths as low 

as a few hundred feet where the formation-fracture gradient is very low. 

The danger is that if the well is in shut-in condition, formation fracturing 

is more likely to occur. This will result in the most severe blowout problem, 

and ultimately an underground blow.

The identification and avoidance of shallow gas will be a principal objec￾tive in well planning and site survey procedures. All drilling programs shall 

contain a clear statement on the probability and risk of encountering shal￾low gas. This will be based on seismic survey and interpretation together 

with offset geological and drilling data. For onshore operations, consid￾eration should be given for carrying out shallow seismic surveys in areas 

of shallow gas risk. In the absence of such surveys, assessment should be 

based on the exploration seismic data, historical well data, and the geo￾logical probability of a shallow gas trap. If shallow 

gas is a likelihood at 

                            

the proposed drilling location, a shallow gas plan specific to company 

and the drilling contractor must be prepared prior to spudding the well. 

Special consideration should be given to: crew positions, training, evacu￾ation plan, and emergency power shut down. For offshore operations, the 

presence of shallow gas can be extremely hazardous especially if no spe￾cific plan of action is prepared prior to spudding of the well. The driller 

will be instructed in writing on what action should be taken if a well kick 

should be noticed while drilling. The problem of drilling a shallow hole is 

that normal indications of a kick are not reliable. For example, penetration 

rates vary tremendously, and mud volume is continuously being added to 

the active system. The most reliable indicator is the differential flow sen￾sor. Due to the difficulties of early detection and the depth of shallow gas 

reservoirs, reaction time is minimal. In such case, extreme caution, and 

alertness are required.

2.1.2.1 Prediction of Shallow Gas Zone

Although the location of gas pockets is difficult to predict, high-resolution 

seismic data acquisition, processing and interpretation techniques increase 

the reliability of the shallow gas prognosis. Therefore, surveys are to be 

recommended. Well proposals should always include a statement on the 

probability of encountering shallow gas, even if no shallow gas is pres￾ent. This statement should not only use the “shallow gas survey”, but also 

include an assessment drawn from the exploration seismic data, historical 

well data, the geological probability of a shallow cap rock, coal formations, 

and any surface indications/seepages. The shallow gas procedures based 

on the shallow gas statement in the well proposal, and practical shallow 

gas procedures should be prepared for that particular well. The following 

guidelines should be adhered to avoid influx and kick: i) avoid shallow 

gas where possible; ii) optimize the preliminary shallow gas investigation; 

iii) the concept of drilling small pilot holes for shallow gas investigation 

with a dedicated unit is considered an acceptable and reliable method of 

shallow gas detection and major problem prevention; iv) surface diverter 

equipment is not yet designed to withstand an erosive shallow gas flow for 

a prolonged period of time. Surface diverters are still seen as a means of 

“buying time” in order to evacuate the drilling site; v) diverting shallow 

gas in subsea is considered to be safer as compared to diverting at surface, 

vi) dynamic kill attempt with existing rig equipment may only be success￾ful if a small pilot hole (e.g., 9 7/8” or smaller) is drilled and immediate 

pumping at maximum rate is applied in the early stage of a kick; and vii) 

riserless top hole drilling in floating drilling operations is an acceptable 

and safe method.

                     Identification of Shallow Gas Pockets

While drilling at shallow depth in a normally pressured formation, no 

indication of a gas pocket can be expected other than higher gas readings 

in the mud returns. Since the overbalance of the drilling fluid at shallow 

depths is usually minimal, pressure surges may cause an underbalanced 

situation which could result in a kick. Therefore, every attempt should be 

made to avoid swabbing. Some definitions are used to describe the risk 

in shallow gas assessment, such as i) high: an anomaly showing all of the 

seismic characteristics of a shallow gas anomaly, that ties to gas in an offset 

well, or is located at a known regional shallow gas horizon, ii) moderate: 

an anomaly showing most of the seismic characteristics of a shallow gas 

anomaly, but which could be interpreted not to be gas and, as such rea￾sonable doubt exists for the presence of gas, iii) low: an anomaly showing 

some of the seismic characteristics of a shallow gas anomaly, but that is 

interpreted not to be gas although some interpretative doubt exists, and 

iv) negligible: either there is no anomaly present at the location or anomaly 

is clearly due to other, nongaseous, causes.

There are two factors that make shallow gas drilling a difficult challenge. 

First, unexpected pressure at the top of the gas-bearing zone, most often 

due to the “gas effect” dictated by zone thickness and/or natural dip, can 

be significant. This pressure is usually unknown, seismic surveys being 

often unable to give an idea either about thickness or in-situ gas concen￾tration. In more complex situations, deep gas may migrate upwards along 

faults. For example, the influx in Sumatra could not be stopped even with 

10.8 ppg mud at very shallow depth because the bit had crossed a fault 

plane. Second, low formation fracture gradients are a predominant factor 

in shallow gas operations.

These two factors result in reduced safety margin for the driller. Minor 

hydrostatic head loss (e.g., swabbing, incorrect hole filling, cement slurry 

without gas-blocking agent), any error in mud weight planning (e.g., gas 

effect not allowed for), or any uncontrolled rate of penetration with sub￾sequent annulus overloading will systematically and quickly result in well 

bore unloading. Shallow gas flows are extremely fast-developing events. 

There is a short transition time between influx detection and well unload￾ing, resulting in much less time for driller reaction and less room for 

error. Poor quality and reliability of most kick-detection sensors worsen 

problems.

Previous history has disclosed the magnitude of severe dynamic loads 

applied to surface diverting equipment, and consequent high probability of 

failure. One of the associated effects is erosion, which leads to high poten￾tial of fire hazards and explosion from flow impingement on rig facilities.

The risk of cratering is a major threat against the stability of bottom￾supported units. As it is impossible to eliminate them (i.e., most shallow 

gas-prone areas are developed from bottom supported units), emphasis 

should be put on careful planning and close monitoring during execution.

2.1.2.3 Case Study

Description: Four new wells were drilled at an offshore platform with cas￾ing on the surface section in batch-drilling mode. 13⅜-in casing shoes 

were set as per plan in a range from 1,800 to 2,000 ft for the four wells 

(Figure 2.1). All the risk-control measures resulting from the risk-analysis 

exercise were implemented when drilling the section. In the first well, 

logging-while-drilling tools were included in the bottomhole assemblies 

(BHA). There were no indications of a shallow gas zone.

Drilling Plan: The plan was to use seawater for the four wells because the 

drilling fluid was for the casing-drilling operation.

Drilling Operations and Potential Problems: Pumping sweeps were 

performed at every connection to help with hole cleaning. Following the 

plans, the first of the four wells was drilled with seawater and sweeps. Soon 

after drilling out of the conductor, fluid losses were experienced.

First Aid Remedy and Consequences: Loss-control material was pumped 

downhole and drilling continued, expecting the coating effect to contribute 

in building a mudcake that would eventually cease the losses. Drilling-fluid 

      

losses decreased but did not stop until section total depth (TD) was reached

and casing was cemented. In addition, when drilling the first well, accurate

position surveys were taken, which required several attempts at every sur￾vey station. These attempts were due to the poor data transmission from

measurement-while-drilling (MWD) tools. The result was an increase of

10% non-productive (e.g., off-bottom) drilling time compared with other

wells. The problems with the MWD transmission also affected the resistiv￾ity and gamma ray data that were planned to provide early information of

any shallow gas accumulation. As a result, it was difficult to interpret the

real-time data provided by the logging tool.

Final Solution: The engineering team decided to change the drilling fluid

from seawater to a low-viscosity mud. They were expecting to build a better

mudcake and to improve fluid-loss control. To improve the MWD transmis￾sion, a low telemetry rate was set on the tools to reduce the time required to

take a survey. These measures contributed to drill the next three wells with

no drilling-fluid losses and with no delays from a lengthy survey procedure.

Lesson Learned: The seawater-and-sweeps system was replaced with a low

viscosity water-based-mud drilling fluid after the problems that had been

faced in the first well. As a result, the three remaining wells were drilled

with improved drilling practices. Severe fluid losses were not observed, and

the quality of the telemetry signal improved substantially. A possible expla￾nation for the problems with the use of seawater are: i) drilling fluid does

not have the required properties to create a consistent mudcake around

the wellbore wall, ii) the use of seawater also induced turbulent flow, which

may give good hole cleaning but would increase the hole washouts in shal￾low formations. An enlarged wellbore and the inability to create an opti￾mum mudcake might have eliminated the coating effect and the expected

improvements in terms of loss control. Problems with the telemetry-signal

quality were attributed to the telemetry rate setup and the noise created by

the drilling fluid. Setting a low telemetry rate in the MWD proved useful

for adapting to the particular condition of casing drilling, where the inter￾nal diameter in the drillstring experiences great variations, such as 2.8 in.

at the BHA and 12.6 in. for the rest of the string.

Personal Experiences: The following are the field experience for diverter

procedures while drilling a top hole. At first sign of flow,

1. Do not stop pumping.

2. Open diverter line to divert/close diverter (both functions

should be interlocked).
                        

            Increase pump strokes to a maximum limit (DO NOT 

exceed maximum pump speed recommended by the manu￾facturer or maximum pressure allowed by relief valve).

4. Switch suction on mud pumps to heavy mud in the reserve 

pit. Zero stroke counter.

5. Raise alarm and announce emergency using the PA system 

and/or inform the rig superintendent. Engage personnel to 

look for gas (Jack-up).

6. If the well appears to have stopped flowing after the heavy 

mud has been displaced stop pumps and observe well.

7. If the well appears to continue to flow after the heavy mud 

has been pumped, carry on pumping from the active system 

and prepare water in a pit for pumping and/or consider pre￾paring pit with heavier mud. When all mud has been con￾sumed, switch pumps to water. Do not stop pumping for as 

long as the well continues to flow.

General Guidelines for Drilling Shallow Gas: The following guidelines 

shall be adhered to while drilling:

Consideration shall be given to drilling a pilot hole with the 

8 ½” or smaller bit size when drilling explorations wells. The 

BHA design shall include a float valve and considerations 

should be given to deviation and subsequent hole opening. 

The major advantages of a small pilot hole are: i) the Rate of 

Penetration (ROP) will be controlled to avoid overloading 

the annulus with cuttings and inducing losses, ii) all losses 

shall be cured prior to drilling ahead. Drilling blind or 

with losses requires the approval from head of operations, 

iii) pump pressure shall be closely monitored and all con￾nections (on jack-up) shall be flow checked, iv) pipe shall be 

pumped out of hole at a moderate rate to prevent swabbing.

General Recommended Drilling Practices in Shallow Gas Areas: 

Common drilling practices, which are applicable for top hole drill￾ing in general and diverter drilling in particular are summarized below. 

Recommendations are made with a view to simplify operations, thereby 

minimizing possible hole problems.

A pilot hole should be drilled in areas with possible shallow 

gas, because the small hole size will facilitate a dynamic well 

killing operation.

      The penetration rate should be restricted. Care should be 

taken to avoid an excessive build-up of solids in the hole that 

can cause formation breakdown and mud losses. Drilling 

with heavier mud returns could also obscure indications of 

drilling through higher pressured formations. The well may 

kick while circulating the hole cleaning. Restricted drilling 

rates also minimize the penetration into the gas-bearing for￾mation which in turn minimizes the influx rate. An excessive 

drilling rate through a formation containing gas reduces the 

hydrostatic head of the drilling fluid, which may eventually 

result in a flowing well.

Every effort should be made to minimize the possibility of 

swabbing. Pumping out of the hole at optimum circulating 

rates is recommended for all upward pipe movements (e.g., 

making connections and tripping). Especially in larger hole 

sizes (i.e., larger than 12”), it is important to check that the 

circulation rate is sufficiently high and the pulling speed is 

sufficiently low to ensure that no swabbing will take place. 

A top drive system will facilitate efficient pumping out of 

hole operations. The use of stabilizers will also increase the 

risk of swabbing; hence the minimum required number of 

stabilizers should be used.

Accurate measurement and control of drilling fluid is most 

important in order to detect gas as early as possible. Properly 

calibrated and functioning gas detection equipment and a 

differential flowmeter are essential in top hole drilling. Flow 

checks are to be made before tripping. At any time, a sharp 

penetration rate may increase or tank level anomaly may be 

observed. When any anomaly appears on the MWD log, it 

is recommended to flow check each connection while drill￾ing the pilot hole in potential shallow gas areas. Measuring 

mud weight in and out, and checking for seepage losses are 

all important practices which shall be applied continuously.

A float valve must be installed in all BHAs which are used 

in top hole drilling in order to prevent uncontrollable flow 

up the drillstring. The float valve is the only down-hole 

mechanical barrier available. The use of two float valves in 

the BHA may be considered in potential shallow gas areas.

Large bit nozzles or no nozzles and large mud pump liners 

should be used to allow lost circulation material (LCM) to be 

pumped through the bit in case of losses. Large nozzles are 

                                    also advantageous during dynamic killing operations, since 

a higher pump rate can be achieved. For example, a pump 

rate of approximately 2,700 l/min at 20,000 kPa pump pres￾sure can be obtained using a 1300–1600 HP pump with 3 

14/32” nozzles installed in the bit. By using 3 18/32” noz￾zles, the pump rate can be increased to around 3,800 ltr/min 

at 20,000 kPa. The use of centre nozzle bits will increase the 

maximum circulation rate even further and also reduces the 

chance of bit balling.

Shallow kick-offs should be avoided in areas with prob￾able shallow gas. Top hole drilling operations in these areas 

should be simple and quick to minimize possible hole prob￾lems. BHAs used for kick-off operations also have flow 

restrictions which will reduce the maximum possible flow 

through the drillstring considerably. A successful dynamic 

well killing operation will then become very unlikely

                                                      

Tarner’s Prediction Method

 Tarner (1944) suggested an iterative technique for predicting cumulative oil produc￾tion Np and cumulative gas production Gp as a function of reservoir pressure. The

method is based on solving the MBE and the instantaneous GOR equation simulta￾neously for a given reservoir pressure drop from a known pressure Pi 1 to an

assumed (new) pressure Pi. It is accordingly assumed that the cumulative oil and gas

production has increased from known values of (Np)i 1 and (Gp)i 1at reservoir

pressure Pi 1 to future values of (Np)i and (Gp)i at the assumed pressure Pi. To

simplify the description of the proposed iterative procedure, the stepwise calculation

is illustrated for a volumetric saturated oil reservoir; however, this method can be

used to predict the volumetric behavior of reservoirs under different driving

mechanisms.

Tarner’s method was preferred to Tracy and Muskat because of the differential

form of expressing each parameter of the material balance equation by Tracy. Also,

Tarner and Muskat method use iterative approach in the prediction until a conver￾gence is reached.

Furthermore, a first approach of the Cumulative Oil Production is needed before

the calculation is performed; a second value of this variable is calculated through the

equation that defines the Cumulative Gas Production, as an average of two different

moments in the production life of the reservoir; this expression, as we will see, is a

function of the Instantaneous Gas Oil Rate, then we need also to calculate this value

in advance from an equation derived from Darcy’s law, this is a very important

relationship since it is strongly affected by the relative permeability ratio between oil

and gas. Finally, both values are compared, if the difference is within certain

predefined tolerance, our first estimate of the Cumulative Oil Production will be

considered essentially right, otherwise the entire process is repeated until the desire

level of accuracy is reached (Tarner 1944).

Tarner’s Prediction Algorithm

Step 1: Select a future reservoir pressure Pi below the initial (current) reservoir

pressure Pi 1 and obtain the necessary PVT data. Assume that the cumulative oil

production has increased from (Np)i 1 to (Np)i. It should be pointed out

that (Np)i 1 and (Gp)i 1 are set equal to zero at the bubble-point pressure

(initial reservoir pressure).

Step 2: Estimate or guess the cumulative oil production (Np)i at Pi.

Step 3: Calculate the cumulative gas production (Gp)i by rearranging the MBE to

give:

Tracy Prediction Method

Tracy (1955) developed a model for reservoir performance prediction that did not

consider oil reservoirs above bubble-point pressure (undersaturated reservoir) but

the computation starts at pressures below or at the bubble-point pressure. To use this

method for predicting future performance, it is pertinent therefore to select future

pressures at desired performance. This means that we need to select the pressure step

to be used. Hence, Tracy’s calculations are performed in series of pressure drops that

proceed from a known reservoir condition at the previous reservoir pressure (Pi 1)

to the new assumed lower pressure (Pi). The calculated results at the new reservoir

pressure becomes “known” at the next assumed lower pressure. The cumulative gas,

oil, and producing gas-oil ratio are calculated at each selected pressure, so the goal is

to determine a table of Np, Gp, and Rp versus future reservoir static pressure.

Tracy’s Prediction Algorithm

Step 1: Select an average reservoir pressure (Pi) of interest

Step 2: Calculate the values of the PVT functions ɸo, ɸg & ɸw where

Schilthuis Prediction Method

Schilthuis develop a method of reservoir performance prediction using the total

produced or instantaneous gas-oil ratio which was defined mathematical as:

Reservoir Performance Prediction

 Introduction

Some of the roles of Reservoir Engineers are to estimate reserve, field development

planning which requires detailed understanding of the reservoir characteristics and

production operations optimization and more importantly; to develop a mathemat￾ical model that will adequately depict the physical processes occurring in the

reservoir such that the outcome of any action can be predicted within reason￾able engineering tolerance of errors. Muskat (1945) stated that one of the functions

of reservoir engineers is to predict the past performance of a reservoir which is still in

the future. Therefore, whether the concept of the engineer is wrong or right, stupid

or clever, honest or dishonest, the reservoir is always right.

We have to bear in mind that reservoirs rarely perform as predicted and as such,

reservoir engineering model has to be updated in line with the production behaviour.

Thus, an accurate prediction of the future 

production rates under various operating

conditions, apply the primary requirement for the oil and gas reservoirs feasibility

evaluation and performance optimization. The conventional method of utilizing

deliverability and material balance equations to predict the production performance

of these reservoirs cannot be utilized often when the complete reservoir data are

lacking.

Reservoir performance prediction is an iterative process. it requires that a con￾vergence criterion must be met after a satisfactory history match is achieved, to be

executed in a short period of time, for a proper optimization of future reservoir

management planning of a field. There are basically four methods of reservoir

performance prediction applying material balance concept and not a numerical

approach where the reservoir is divided into grid blocks. These are:

• Tracy method

• Muskat method

• Tarner method

• Schilthuis method

All the techniques used to predict the future performance of a reservoir are based

on combination of appropriate MBE with the instantaneous GOR using the proper

saturation equation. The calculations are repeated at a series of assumed reservoir

pressure drops. These calculations are usually based on stock-tank barrel of oil-in￾place at the bubble-point pressure. Above the bubble point pressure, the cumulative

oil produced is calculated directly from the material balance equations as presented

in Craft & Hawkins (1991), Dake (1978), Tarek (2010), Cole (1969), Cosse (1993),

Economides et al. (1994) & Hawkins (1955). The MBE for undersaturated reservoir

are expressed below.

11.1.1 For Undersaturated Reservoir (P > Pb) with No Water

Influx

That is above the bubble point; the assumptions made are:

In applying the above methods of prediction for saturated reservoirs, we require

some additional information to match the previous field production data in order to

predict the future. Such relations are the instantaneous gas-oil ratio (GOR), equation

relating the cumulative GOR to the instantaneous GOR and the equation that relates

saturation to cumulative oil produced.

On the contrary, despite the fact that the material balance equation is a tool used

by the reservoir engineers, there are some aspects which were not put into consid￾eration when performing prediction performance. These are:

• The contribution of the individual well’s production rate

• The actual number of wells producing from the reservoir

• The positions of these wells in the reservoir are not considered since it is assume

to be a tank model

• The time it will take to deplete the reservoir to an abandonment pressure

• Does not see faults in the reservoir if there is any and the variation in rock and

fluid properties.

Instantaneous Gas- Oil Ratio

Instantaneous gas-oil ratio at any time, R is defined as the ratio of the standard cubic

feet of gas produced to the stock tank barrel of oil produced at that same instant of

time and reservoir pressure. The gas production comes from solution gas and free

gas in the reservoir which has come out of the solution (Tarek, 2010).

Instantaneous producing GOR is given mathematically as

Muskat’s Prediction Method

In 1945, Muskat developed a method for reservoir performance prediction at any

stage of pressure depletion by expressing the material balance equation for a

depletion-drive reservoir in differential form as derived below.

The oil pore volume (original volume of oil in the reservoir) is given as:

Muskat’s Prediction Algorithm

At any given pressure, Craft et al. (1991) developed the following algorithm for

solving Muskat’s equation:

Step 1: Obtain relative permeability data at corresponding saturation values and then

make a plot of krg/kro versus saturation.

Step 2: Make a plot of fluid properties {Rs, Bo and (1/Bg)} versus pressure and

determine the slope of each plot at selected pressures, i.e., dBo/dp, dRs/dp, and d

(1/Bg)/dp.

Step 3: Calculate the pressure dependent terms X(p), Y(p), and Z(p) that correspond

to the selected pressures in Step 2.

History Matching

 The update of a model to fit the actual performance is known as history matching.

Clearly speaking, developing a model that cannot accurately predict the past perfor￾mance of a reservoir within a reasonable engineering tolerance of error is not a good

tool for predicting the future of the same reservoir. To history match a given field

data with material balance equation, we have to state clearly the known parameters to

match and the unknown parameters to tune to get the field historical production data

with minimum tolerance of error and these parameters are given in Table 10.1.

Besides, one of the paramount roles of a reservoir engineer is to forecast the future

production rates from a specific well or a given reservoir. From history, engineers

have formulated several techniques to estimate hydrocarbon reserves and future

performance. The approaches start from volumetric, material balance, decline

curve analysis techniques to sophisticated reservoir simulators. Whatever approach

taken by the engineers to predict production rates and reservoir performance pre￾dictions whether simple or complex method used relies on the history match.

The general approach by the engineer whose production history is already

available, is to determine the rates for the given period of production. The value

calculated is use to validate the actual rates and if there is an agreement, the rate is

assumed to be correct. Thus, it is then used to predict the future production rates. On

the contrary, if there is no agreement between the calculated and the actual rates, the

calculation is repeated by modifying some of the key parameters. This process of

matching the computed rate with the actual observed rate is called history matching.

It therefore implies that history matching is a process of adjusting key properties

of the reservoir model to fit or match the actual historic data. It helps to identify the

weaknesses in the available data, improves the reservoir description and forms basis

for the future performance predictions. One of these parameters that is vital in history

matching, is the aquifer parameters that are not always known. Hence, modification

of one or several of these parameters to obtain an acceptable match within reasonable

engineering tolerance of error or engineering accuracy is history matching (Donnez

2010). Therefore, to complete this chapter, the following textbooks and articles were

reviewed: Aziz & Settary (1980), Crichlow (1977), Kelkar & Godofredo (2002),

Chavent et al. (1973), Chen et al. (1973), Harris (1975), Hirasaki (1973),

Warner et al. (1979), Watkins et al. (1992).

History Matching Plan

The validity of a model should be approach in two phases: pressure match and

saturation match (oil, gas and water rates). The pressure and saturation phases

matche, follows different pattern depending on purpose (experience of the individual

carrying out the study). The simulation follows the same basic steps for the two

phases. These steps include:

• Gather data

• Prepare analysis tools

• Identify key wells/tank

Interpret reservoir behavior from observed data

• Run model

• Compare model results to observed data

• Adjust models parameters

10.3 Mechanics of History Matching

There are several parameters that are varied either singly or collectively to minimize

the differences between the observed data and those calculated data by the simulator.

Modifications are usually made on the following areas as presented by Crichlow

(1977):

• Rock data modifications (permeability, porosity, thickness & saturations)

• Fluid data modifications (compressibility, PVT data & viscosity)

• Relative permeability data

• Shift in relative permeability curve (shift in critical saturation data)

• Individual well completion data (skin effect & bottom hole flowing pressure)

The two fundamental processes which are controllable in history matching are as

follows:

1. The quantity of fluid in the system at any time and its distribution within the

reservoir, and

2. The movement of fluid within the system under existing potential gradients

(Crichlow 1977).

The manipulation of these two processes enables the engineer to modify any of

the earlier-mentioned parameters which are criteria to history matching. It is man￾datory that these modifications of the data reflect good engineering judgment and be

within reasonable limits of conditions existing in that area. History matching is

actually an act and time consuming. This implies that the total time spent on history

matching depends largely on the expertise of the engineer and his familiarity with the

particular reservoir. Here are some of the key variables to consider when conducting

history matching:

• Porosity (local)

• Water Saturation (Global)

• Permeability (Local)

• Gross Thickness (Local)

• Net Thickness (Local)

• kv/kh Ratio (Global


Local?)

• Transmissibility (x/y/z/) (Local)

• Aquifer Connectivity and Size (Regional)

• Pore Volume (Local)

• Fluid Properties (Global)

• Rock Compressibility (Global)

Relative Permeability (Global -regional with Justification)

• Capillary Pressure (Global -regional with justification)

• Mobile Oil Volume (Global or Local?)

• Datum Pressure (Global)

• Original Fluid Contact (Global)

• Well Inflow Parameters (Local)

10.4 Quantification of the Variables Level of Uncertainty

The following variables are often considered to be determinate (low uncertainty):

• Porosity

• Gross thickness

• Net thickness

• Structure (reservoir top/bottom/extent)

• Fluid properties

• Rock compressibility

• Capillary pressure

• Datum pressure

• Original fluid contact

• Production rates

The following variables are often considered to be indeterminate (high

uncertainty):

• Pore volume

• Permeability

• Transmissibility

• Kv/Kh ratio

• Rel. perm. curves

• Aquifer properties

• Mobile oil volumes

• Well inflow parameters

10.5 Pressure Match

Here are two proposed option for pressure match

Option 1

• Run the model under reservoir voidage control

• Examine the overall pressure levels

• Adjust the pore volume/aquifer properties to match overall pressure

Match the well pressures

• Modify local PVs/aquifers to match overall pressures

• Modify local transmissibility to match pressure gradient

Option 2

• Check/Initialization

• Run simulation model

• Adjust Kx for well which cannot meet target rates

• Adjust pore volume and compressibility to match pressure change with time

• Adjust Kv and Tz to capture vertical pressure gradient

• Adjust Kv and Tz to meet areal pressure

• Adjust Tx and Ty at the faults

• Adjust PI’s to meet production allocations

• Iterate

10.6 Saturation Match

Option 1

• Normally attempted once pressures matched

• Most important parameters are relative permeability curves and permeabilities

• Try to explain the reasons for the deviations and act accordingly

• Changes to relative permeability tables should affect the model globally

• Changes to permeabilities should have some physical justification

• Consider the use of well pseudos

• Assumed layer KH allocations may be incorrect (check PLTs, etc.)

Option 2

• Check/Initialization Model

• Run simulation model

• Check overall model water/gas movement(process physics)

• Adjust relative permeability

• Introduce and adjust well’s relative permeabilities (Krs) to match individual well

performance

• Adjust PI’s to match production allocation

• Add or delete completion layers to account for channeling, leaking plugs

• Iterate

Well PI Match

• Not usually matched until pressures and saturations are matched, unless BHP

affects production rates

• Must be matched before using model in prediction mode

• Match FBHP data by modifying KH, skin or PI directly

10.8 Problems with History Matching

• Non uniqueness of accepted match

• Lack of reliable field data

• Available data may be limited

• Errors in simulator can cause a correct set of parameters to yield incorrect result.

10.9 Review Data Affecting STOIIP

Verify that the value of STOIIP calculated by the model is in line with estimated

values by volumetric calculations and material balance. If the calculated value is too

high/low, this is normally due to errors of the following type:

• High/low porosity values (data entry format error)

• Misplace fluid contacts (gas-oil and/or water-oil)

• Inclusion/exclusion of grid blocks that belong or not to the reservoir model.

• High/low values in the capillary pressure curves.

• Errors in net sand thickness.

10.9.1 Problems and Likely Modifications

• Localised high pressure area and localised low pressure area.

– Remedies:

– Modify k to allow case of flow from high pressure region to low pressure

region

– Reduce oil in high pressure region by changing ϕ or h or So or all of them.

– If rock data are varied, there may be need for redigitizing.

• Generally high pressure in the whole system

Remedy:

• Reduce oil in place by reducing porosity in the whole system.

– Discontinuous pressure distribution

Remedy: increase k to smoothen effect

• Model runs out of fluid

Remedy:

– Increase initial fluid saturation. Fluid contacts may be varied.

• No noticeable drawdown in pressure even after considerable withdrawal.

Remedy:

– Error in compressibility entered.

• Sw increase without any injection or influx of water.

Remedy:

– Increase rock compressibility used.

• Problem with matching GOR, WOR

Remedy:

– Modify relative permeability

If simulated GOR > observed GOR, reduce Krg vale in the simulator. The reverse

is true.

If free gas starts flowing early, increase critical gas sat. The reverse is also

the case.

After everything has been done, observed pressures and production are greater

than the model.

Cause:

• Reservoir getting energy from region not defined for example, fluid influx

Remedy:

• Redefine area and model or include aquifer if observed water cut is increasing.

10.10 Methods of History Matching

The method adopted for matching a field’s historic data depends on the engineer in

question. History matching has been improved from manual turning of some param￾eters to a more sophisticated computer aided tool. Today, some engineers still use

manual turning which work well for them rather than the computer aided history

matching.

10.10.1 Manual History Matching

During manual history matching, changing one or two parameters manually by trial￾and error can be tedious and inconsistent with the geological models. To make the

parameters best fit with the simulated and observed data gives considerable uncer￾tainties and does not have the reliability for a longer period.

10.10.2 Automated History Matching

Automated history matching is much faster and requires fewer simulation runs than

manual history matching. It includes a large number of different parameters and

tackles a large number of wells without problems. In manual history matching, one

or two parameters are varied at a time and it would require preliminary analysis first

for tackling the wells.

Besides, automatic history matching could give more reliable results in the case

of complex lithology conditions with considerable heterogeneity. The basic process

in automatic history matching is to start from an initial parameter guess and then

improve it by integrating field data in an automatic loop. In this case, parameter

changes are done by computer programming to minimize the function to show

differences between simulated and observed data. This is called objective function

that includes both model mismatch and data mismatch parts.

10.10.3 Classification of Automatic History Matching

• Deterministic Algorithm

• Stochastic Algorithm

10.10.3.1 Deterministic Algorithm

Deterministic algorithms use traditional optimization approaches and obtain one

local optimum reservoir model within the number of simulation iteration constraints.

In implementation, the gradient of the objective function is calculated and the

direction of the optimization search is then determined (Liang 2007). The gradient

based algorithms minimize the difference between the observed and simulated

measurements which is called the minimization of the objective function that

considered the following loop:

• To run the flow simulator for the complete history matching period,

• To evaluate the cost function,

• To update the static parameters and go back to the first step.

The following are the list of several algorithms that are commonly used for the

basis of gradient based algorithms (Landa 1979; Liang 2007):

• Gradient based algorithms:

– Steepest Descent

– Gauss-Newton (GN)

– Levenberg-Marquardt

– Singular Value Decomposition

– Particle Swarm Optimization

– Conjugate Gradient

– Quasi-Newton

– Limited Memory Broyden Fletcher Goldfarb Shanno (LBFGS)

– Gradual Deformation

10.10.3.2 Stochastic Algorithm

The stochastic algorithm takes considerable amounts of computational time com￾pared to a deterministic algorithm, but due to the rapid development of computer

memory and computation speed, stochastic algorithms are receiving more and more

attention.

Stochastic algorithms have three main direct advantages:

• The stochastic approach generates a number of equal probable reservoir models

and therefore is more suitable to non-unique history matching problems,

• It is straight-forward to quantify the uncertainty of performance forecasting by

using these equal probable model,

• Stochastic algorithms theoretically reach the global optimum.

The following are list of several algorithms that are commonly used on the basis

of non-gradient based stochastic algorithms (Landa 1979; Liang 2007):

• Non-gradient based algorithms:

– Simulated Annealing

– Genetic Algorithm

– Polytope

– Scatter & Tabu Searches

– Neighborhood

– Kalman Filter

How Do We Improve the Productivity Index?

 This can be done by altering the parameters in the flow equation. Thus, for the well

productivity or inflow performance to be improved, we need to carry out any of the

following:

• Acid stimulation to remove skin

• Increasing the effective permeability around the wellbore

• Reduction in fluid viscosity

• Reduction in the formation volume factor

• Increasing the well penetration

A case study of an improvement to IPR curve of a well

Well k35 result for before and after stimulation

Inflow Performance Relationship

Introduction

Subsurface production of hydrocarbon has to do with the movement of fluid from the

reservoir through the wellbore to the wellhead. This fluid movement is divided into

two as depicted in Fig. 9.1.

The flow of fluids (hydrocarbons) from the reservoir rock to the wellbore is

termed the inflow. The inflow performance represents fluid production behavior of

a well’s flowing pressure and production rate. This differs from one well to another

especially in heterogeneous reservoirs. The Inflow Performance Relationship (IPR)

for a well is the relationship between the flow rate of the well (q), average reservoir

pressure (Pe) and the flowing pressure of the well (Pwf). In single phase flow, this

relationship is a straight line but when gas is moving in the reservoir, at a pressure

below the bubble point, this is not a linear relationship.

A well starts flowing if the flowing pressure exceeds the backpressure that the

producing fluid exerts on the formation as it moves through the production system.

When this condition holds, the well attains its absolute flow potential.

The backpressure or bottomhole pressure has the following components:

• Hydrostatic pressure of the producing fluid column

• Friction pressure caused by fluid movement through the tubing, wellhead and

surface equipment

• Kinetic or potential losses due to diameter restrictions, pipe bends or elevation

changes.

The IPR is often required for estimating well capacity, designing well comple￾tion, designing tubing string, optimizing well production, nodal analysis calcula￾tions, and designing artificial lift.

Factors Affecting IPR

Factors influencing the shape of the IPR are the pressure drop, viscosity, formation

volume factor, skin and relative permeability across the reservoir.

There are several existing empirical correlations developed for IPR. This are:

9.3 Straight Line IPR Model

When the flow rate is plotted against the pressure drop, it gives a straight line from

the origin with slope as the productivity index as shown in the figure below.

Steps for Construction of Straight Line IPR

Step 1: Obtain a stabilize flow test data

Step 2: Determine the well productivity

Step 3: Assume different pressure value to zero in a tabular form

Step 4: Calculate the rate corresponding to the assume pressure

Step 5: Make a plot of rate versus pressure

9.4 Wiggins’s Method IPR Model

Wiggins (1993) developed the following generalized empirical three phase IPR

similar to Vogel’s correlation based on his developed analytical model in 1991:

For Oil

Klins and Majcher IPR Model

Based on Vogel’s work, Klins and Majcher (1992) developed the following IPR that

takes into account the change in bubble-point pressure and reservoir pressure.

Standing’s Method

The model developed by Standing (1970) to predict future inflow performance

relationship of a well as a function of reservoir pressure was an extension of Vogel’s

model (1968).

Vogel’s Method

Undersaturated Oil Reservoir

An undersaturated reservoir is a system whose pressure is greater than the bubble

point pressure of the reservoir fluid. For the fact that the pressure of the reservoir is

greater than the bubble point pressure does not mean that as production increases for

a period of time, the pressure will not go below the bubble point pressure. Hence,

careful evaluation will lead to a right decision and vice versa.

Since the reservoirs are tested regularly, it means that the stabilized test can be

conducted below or above the bubble point pressure. Thus, for:

Case: pressure above bubble point

From stabilized test data point, the productivity index is:

Vogel IPR Model for Saturated Oil Reservoirs

This is a reservoir whose pressure is below the bubble point pressure of the fluid. In

this case, we calculate the maximum oil flow rate from the stabilized test and then

generate the IPR model. Mathematically

Fetkovich’s Model

According to Tarek (2010), the model developed by Fetkovich in 1973 for under￾saturated and saturated region, was an expansion of Muskat and Evinger (1942)

model derived from pseudosteady-state flow equation to observe the IPR nonlinear

flow behavior.

9.8.1 Undersaturated Fetkovich IPR Model

Saturated Fetkovich IPR Model

Cheng Horizontal IPR Model

Cheng (1990) presented a form of Vogel’s equation for horizontal wells that is based

on the results of a numerical simulator. The proposed expression has the following

form

 

Pressure Regimes and Fluid Contacts

Introduction

The main source of energy during primary hydrocarbon recovery is the pressure of

the reservoir. At any given time in the reservoir, the average reservoir pressure is an

indication of how much gas, oil or water is remaining in the porous rock media. This

represents the amount of the driving force available to push the remaining hydro￾carbon out of the reservoir during a production sequence. Most reservoir systems are

identified to be heterogeneous and it is worthy to note that the magnitude and

variation of pressure across the reservoir is a paramount aspect in understanding

the reservoir both in exploration and development (production) phases (Fig. 8.1).

Hydrocarbon reservoirs are discovered at some depths beneath the earth crust as a

result of depositional process and thus, the pore pressure of a fluid is developed

within a rock pore space due to physical, chemical and geologic processes through

time over an area of sediments. There are three identified pressure regimes:

• Normal (relative to sea level and water table level, i.e. hydrostatic)

• Abnormal or overpressure (i.e. higher than hydrostatic)

• Subnormal or underpressure (i.e. lower than hydrostatic)

Fluid pressure regimes in hydrocarbon columns are dictated by the prevailing

water pressure in the vicinity of the reservoir (Bradley 1987). In a perfectly normal

pressure zone, the water pressure at any depth can be calculated as:

Pressure Regime of Different Fluids

Some Causes of Abnormal Pressure

• Incomplete compaction of sediments

Fluids in sediments have not escaped and are still helping to support the overburden.

• Aquifers in Mountainous Regions

Aquifer recharge is at higher elevation than drilling rig location.

• Charged shallow reservoirs due to nearby underground blowout.

• Large structures

• Tectonic movements

Abnormally high pore pressures may result from local and regional tectonics. The

movement of the earth’s crustal plates, faulting, folding, lateral sliding and slipping,

squeezing caused by down dropped of fault blocks, diapiric salt and/or shale

movements, earthquakes, etc. can affect formation pore pressures.

Due to the movement of sedimentary rocks after lithification, changes can occur

in the skeletal rock structure and interstitial fluids. A fault may vertically displace a

fluid bearing layer and either create new conduits for migration of fluids giving rise

to pressure changes or create up-dip barriers giving rise to isolation of fluids and

preservation of the original pressure at the time of tectonic movement.

When crossing faults, it is possible to go from normal pressure to abnormally high

pressure in a short interval. Also, thick, impermeable layers of shale (or salt) restrict

the movement of water. Below such layers abnormal pressure may be found. High

pressure occurs at the upper end of the reservoir and the hydrostatic pressure gradient

is lower in gas or oil than in water.

8.4 Fluid Contacts

In the volumetric estimation of a field’s reserve, the initial location of the fluid

contacts and also for the field development, the current fluid contacts are very critical

factor for adequate evaluation of the hydrocarbon prospect. Typically, the position of

fluid contacts are first determined within control wells and then extrapolated to other

parts of the field. Once initial fluid contact elevations in control wells are determined,

the contacts in other parts of the reservoir can be estimated. Initial fluid contacts

within most reservoirs having a high degree of continuity are almost horizontal, so

the reservoir fluid contact elevations are those of the control wells.

Estimation of the depths of the fluid contacts, gas/water contact (GWC), oil/water

contact (OWC), and gas/oil contact (GOC) can be made by equating the pressures of

the fluids at the said contact. Such that at GOC, the pressure of the gas is equal to the

pressure of the oil and the same concept holds for OWC.

Methods of Determining Initial Fluid Contacts

8.4.1.1 Fluid Sampling Methods

This is a direct measurement of fluid contact such as: Production tests, drill stem

tests, repeat formation tester (RFT) tests (Schlumberger, 1989). These methods have

some limitation which are:

• Rarely closely spaced, so contacts must be interpolated

• Problems with filtrate recovery on DST and RFT

• Coring, degassing, etc. may lead to anomalous recoveries

8.4.1.2 Saturation Estimation from Wireline Logs

It is the estimation of fluid contacts from the changes in fluid saturations or mobility

with depth, it is low cost and accurate in simple lithologies and rapid high resolution

but have limitations as:

• Unreliable in complex lithologies or low resistivity sands

• Saturation must be calibrated to production

8.4.1.3 Estimation from Conventional and Sidewall Cores

Estimates fluid contacts from the changes in fluid saturation with depth which can be

related to petrophysical properties. It can estimates saturation for complex litholo￾gies (Core Laboratories, 2002). The limitations are:

• Usually not continuously cored, so saturation profile is not as complete

• Saturation measurements may not be accuratPressure Methods

There are basically two types of pressure methods: the pressure profiles from repeat

formation tester and pressure profiles from reservoir tests, production tests and drill

stem tests.

8.4.1.5 Pressure Profiles from Repeat Formation Tester

It estimates free water surface from inflections in pressure versus depth curve.

8.4.1.6 Pressure Profiles from Reservoir Tests, Production Tests

and Drill Stem Tests

It estimates free water surface from pressures and fluid density measurements which

makes use of widely available pressure data.

Both pressure techniques are pose with limitations such as:

• Data usually require correction

• Only useful for thick hydrocarbon columns

• Most reliable for gas contacts, Requires many pressure measurements for profile,

Requires accurate pressurese

Estimate the Average Pressure from Several Wells

in a Reservoir

When dealing with oil, the average reservoir pressure is only calculated with material

balance when the reservoir is undersaturated (i.e when the reservoir pressure is

above the bubble point pressure). Average reservoir pressure can be estimated in

two different ways but are not covered in this book (see well test analysis textbooks

for details).

• By measuring the long-term buildup pressure in a bounded reservoir. The buildup

pressure eventually builds up to the average reservoir pressure over a long enough

period of time. Note that this time depends on the reservoir size and permeability

(k) (i.e. hydraulic diffusivity).

• Calculating it from the material balance equation (MBE) is given below

For a gas well

   

Decline Curve Analysis

 Introduction

Globally, the oil and gas production profiles differ considerably. When a field starts

production, it builds up to a plateau state, and every operator will want to remain in

this stage for a very long period of time if possible. But in reality, it is practically not

possible, because, at a point in the life of the field, the production rate will eventually

decline to a point at which it no longer produces profitable amounts of hydrocarbon

as shown in Fig. 7.1. In some fields, the production build-up rate starts in the first few

years, most fields’ profiles have flat top and the length of the flat top depends on

reservoir productivity.

Some fields have long producing lives depending upon the development plan of

the field and reservoir characteristics such as the reservoir, drive mechanism. Wells

in water-drive and gas-cap drive reservoirs often produce at a near constant rate until

the encroaching water or expanding gas cap reaches the well, thereby causing a

sudden decline in oil production. Wells in gas solution drive and oil expansion drive

reservoirs have exponential or hyperbolic declines: rapid declines at first, then

leveling off.

Therefore, decline curve analysis can be defined as a graphical procedure used for

analyzing the rates of declining production and also a means of predicting future oil

well or gas well production based on past production history. Production decline

curve analysis is a traditional means of identifying well production problems and

predicting well performance and life based on measured oil or gas well production.

Today, several computer software have been built to perform this task and prior to

the availability of computers, decline curve analysis was performed by hand on

semi-log plot paper. Several authors (Rodriguez & Cinco-Ley (1993), Mikael

(2009), Duong (1989) have developed new models or approach for production

decline analysis. Agarwal et al. (1998) combined type curve and decline curve

analysis concepts to analyse production data. Doublet et al. (1994), applied the

material balance time for a field using decline curve analysis.

Furthermore, as stated by Thompson and Wright (1985), decline curve is one of

the oldest methods of predicting oil reserves with the following advantages:

• They use data which is easy to obtain

• They are easy to plot

• They yield results on a time basis, and

• They are easy to analyze.

7.2 Application of Decline Curves

• Production decline curve illustrates the amount of oil and gas produced per unit

of time.

• If the factors affecting the rate of production remaining constant, the curve will be

fairly regular, and, if projected, can give the future production of the well with an

assumption that the factors that controlled production in the past will continue to

do so in future.

• The above knowledge is used to ascertain the value of a property and proper

depletion and depreciation charges may be made on the books of the operating

company.

• The analysis of the production decline curve is employed to determine the value

in oil and gas wells economics.

• Identify well production problems

• Decline curves are used to forecast oil and gas production for the reservoir and on

per well basis and field life span.

• Decline curves are also used to predict oil and gas reserves; this can be used as a

control on the volumetric reserves calculated from log analysis results and

geological contouring of field boundaries.

• It is often used to estimate the recovery factor by comparing ultimate recovery

with original oil in place or gas in place calculations

Causes of Production Decline

• Changes in bottom hole pressure (BHP), gas-oil ratio (GOR), water-oil ratio

(WOR), Condition in drilling area

• Changes in Productivity Index (PI)

• Changes in efficiency of vertical & horizontal flow mechanism or changes in

equipment for lifting fluid.

• Loss of wells

7.4 Reservoir Factors that Affect the Decline Rate

• Pressure depletion

• Number of producing wells

• Reservoir drive mechanism

• Reservoir characteristics

• Saturation changes and

• Relative permeability.

7.5 Operating Conditions that Influence the Decline Rate

• Separator pressure

• Tubing size

• Choke setting

• Workovers

• Compression

• Operating hours, and

• Artificial lift.

As long as the above conditions do not change, the trend in decline can be analyzed

and extrapolated to forecast future well performance. If these conditions are altered,

for example; through a well workover, the decline rate determined during

pre-workover will not be applicable to the post-workover period.

7.6 Types of Decline Curves

Arps (1945) proposed that the “curvature” in the production-rate-versus-time curve

can be expressed mathematically by a member of the hyperbolic family of equations.

Arps recognized the following three types of rate-decline behavior:

Exponential decline

• Harmonic decline

• Hyperbolic decline

Arps introduces equations for each type and used the concept of loss-ratio and its

derivative to derive the equations. The three declines have b values ranging from 0 to

1. Where b ¼ 0 represents the exponential decline, 0 < b < 1 represents the

hyperbolic decline, and b ¼ 1 represents the harmonic decline (Fig. 7.2).

The plots of production data such as log(q) versus t; q versus Np; log(q) versus

log(t); Np versus log(q) are used to identify a representative decline model.

7.6.1 Identification of Exponential Decline

If the plot of log(q) versus t OR q versus Np shows a straight line (see figures below)

and in accordance with the respective equations, the decline data follow an expo￾nential decline model.

Mathematical Expressions for the Various Types of Decline

Curves

The three models are related through the following relative decline rate equation

(Arps 1945):

Relationship Between Nominal and Effective Decline Rate

The nominal decline rate (Di) is defined as the negative slope of the curvature

representing the natural logarithm of the production rate versus time

Cumulative Production for Exponential Decline

The Integration of the production rate over time gives an expression for the cumu￾lative oil production as:

Steps for Exponential Decline Curve Analysis

The following steps are taken for exponential decline analysis, for predicting future

flow rates and recoverable reserves (Tarek, 2010):

• Plot flow rate vs. time on a semi-log plot (y-axis is logarithmic) and flow

rate vs. cumulative production on a cartesian (arithmetic coordinate) scale.

• Allowing for the fact that the early time data may not be linear, fit a straight line

through the linear portion of the data, and determine the decline rate “D” from the

slope (b/2.303) of the semi-log plot, or directly from the slope (D) of the rate￾cumulative production plot.

• Extrapolate to q ¼ qt to obtain the recoverable hydrocarbons.

• Extrapolate to any specified time or abandonment rate to obtain a rate forecast and

the cumulative recoverable hydrocarbons to that point in time

7.7.2 Harmonic Decline Rate

Cumulative Production for Harmonic Decline

The expression for the cumulative production for a harmonic decline is obtained by

integration of the production rate. This is given by:

Hyperbolic Decline

The hyperbolic decline model is inferred when 0 < b < 1

Hence the integration of